There are typically tradeoffs between time and space when compressing data. Therefore, as long as data is compressible, more time can be invested in order to improve the compression and thereby saving more space. Many compression algorithms typically have several modes, ranging between fast and slow, with corresponding compression results.
One commonly used compression method is the Lempel-Ziv 77 factorization. One technique utilized by the Lempel-Ziv 77 factorization is replacing a long repetition with a short pointer in order to save space. The longer the repetition, the more space can be saved by replacing it with a pointer. In operation, the effort invested in finding the longest possible repetition is one of the major variables in the time vs. space tradeoff described supra. For example, higher levels of compression typically allocate more resources towards finding longer repetitions.
The description above is presented as a general overview of related art in this field and should not be construed as an admission that any of the information it contains constitutes prior art against the present patent application.